For EIP-4844, Ethereum shoppers want the flexibility to compute and confirm KZG commitments. Relatively than every consumer rolling their very own crypto, researchers and builders got here collectively to put in writing c-kzg-4844, a comparatively small C library with bindings for higher-level languages. The concept was to create a sturdy and environment friendly cryptographic library that every one shoppers may use. The Protocol Safety Analysis crew on the Ethereum Basis had the chance to evaluation and enhance this library. This weblog put up will focus on some issues we do to make C tasks safer.
Fuzz
Fuzzing is a dynamic code testing approach that entails offering random inputs to find bugs in a program. LibFuzzer and afl++ are two fashionable fuzzing frameworks for C tasks. They’re each in-process, coverage-guided, evolutionary fuzzing engines. For c-kzg-4844, we used LibFuzzer since we have been already well-integrated with LLVM venture’s different choices.
This is the fuzzer for verify_kzg_proof, one in every of c-kzg-4844’s features:
#embrace "../base_fuzz.h" static const size_t COMMITMENT_OFFSET = 0; static const size_t Z_OFFSET = COMMITMENT_OFFSET + BYTES_PER_COMMITMENT; static const size_t Y_OFFSET = Z_OFFSET + BYTES_PER_FIELD_ELEMENT; static const size_t PROOF_OFFSET = Y_OFFSET + BYTES_PER_FIELD_ELEMENT; static const size_t INPUT_SIZE = PROOF_OFFSET + BYTES_PER_PROOF; int LLVMFuzzerTestOneInput(const uint8_t* information, size_t measurement) { initialize(); if (measurement == INPUT_SIZE) { bool okay; verify_kzg_proof( &okay, (const Bytes48 *)(information + COMMITMENT_OFFSET), (const Bytes32 *)(information + Z_OFFSET), (const Bytes32 *)(information + Y_OFFSET), (const Bytes48 *)(information + PROOF_OFFSET), &s ); } return 0; }
When executed, that is what the output appears like. If there have been an issue, it will write the enter to disk and cease executing. Ideally, it is best to have the ability to reproduce the issue.
There’s additionally differential fuzzing, which is a way which fuzzes two or extra implementations of the identical interface and compares the outputs. For a given enter, if the output is totally different, and also you anticipated them to be the identical, you already know one thing is flawed. This system could be very fashionable in Ethereum as a result of we wish to have a number of implementations of the identical factor. This diversification gives an additional degree of security, understanding that if one implementation have been flawed the others could not have the identical problem.
For KZG libraries, we developed kzg-fuzz which differentially fuzzes c-kzg-4844 (by its Golang bindings) and go-kzg-4844. Up to now, there have not been any variations.
Protection
Subsequent, we used llvm-profdata and llvm-cov to generate a protection report from operating the exams. It is a nice strategy to confirm code is executed (“coated”) and examined. See the coverage goal in c-kzg-4844’s Makefile for an instance of find out how to generate this report.
When this goal is run (i.e., make protection) it produces a desk that serves as a high-level overview of how a lot of every perform is executed. The exported features are on the high and the non-exported (static) features are on the underside.
There may be plenty of inexperienced within the desk above, however there may be some yellow and purple too. To find out what’s and is not being executed, consult with the HTML file (protection.html) that was generated. This webpage exhibits your complete supply file and highlights non-executed code in purple. On this venture’s case, a lot of the non-executed code offers with hard-to-test error circumstances reminiscent of reminiscence allocation failures. For instance, this is some non-executed code:
At first of this perform, it checks that the trusted setup is large enough to carry out a pairing test. There is not a check case which gives an invalid trusted setup, so this does not get executed. Additionally, as a result of we solely check with the right trusted setup, the results of is_monomial_form is at all times the identical and does not return the error worth.
Profile
We do not advocate this for all tasks, however since c-kzg-4844 is a efficiency essential library we predict it is essential to profile its exported features and measure how lengthy they take to execute. This may help establish inefficiencies which may probably DoS nodes. For this, we used gperftools (Google Efficiency Instruments) as an alternative of llvm-xray as a result of we discovered it to be extra feature-rich and simpler to make use of.
The next is an easy instance which profiles my_function. Profiling works by checking which instruction is being executed occasionally. If a perform is quick sufficient, it will not be seen by the profiler. To scale back the possibility of this, you might have to name your perform a number of instances. On this instance, we name my_function 1000 instances.
#embrace <gperftools/profiler.h> int task_a(int n) { if (n <= 1) return 1; return task_a(n - 1) * n; } int task_b(int n) { if (n <= 1) return 1; return task_b(n - 2) + n; } void my_function(void) { for (int i = 0; i < 500; i++) { if (i % 2 == 0) { task_a(i); } else { task_b(i); } } } int essential(void) { ProfilerStart("instance.prof"); for (int i = 0; i < 1000; i++) { my_function(); } ProfilerStop(); return 0; }
Use ProfilerStart(“<filename>”) and ProfilerStop() to mark which components of your program to profile. When re-compiled and executed, it is going to write a file to disk with profiling information. You possibly can then use pprof to visualise this information.
Right here is the graph generated from the command above:
This is an even bigger instance from one in every of c-kzg-4844’s features. The next picture is the profiling graph for compute_blob_kzg_proof. As you’ll be able to see, 80% of this perform’s time is spent performing Montgomery multiplications. That is anticipated.
Reverse
Subsequent, view your binary in a software program reverse engineering (SRE) instrument reminiscent of Ghidra or IDA. These instruments may help you perceive how high-level constructs are translated into low-level machine code. We predict it helps to evaluation your code this fashion; like how studying a paper in a special font will pressure your mind to interpret sentences otherwise. It is also helpful to see what sort of optimizations your compiler makes. It is uncommon, however typically the compiler will optimize out one thing which it deemed pointless. Hold a watch out for this, one thing like this truly occurred in c-kzg-4844, some of the tests were being optimized out.
Once you view a decompiled perform, it is not going to have variable names, advanced sorts, or feedback. When compiled, this data is not included within the binary. It is going to be as much as you to reverse engineer this. You will usually see features are inlined right into a single perform, a number of variables declared in code are optimized right into a single buffer, and the order of checks are totally different. These are simply compiler optimizations and are typically advantageous. It might assist to construct your binary with DWARF debugging data; most SREs can analyze this part to supply higher outcomes.
For instance, that is what blob_to_kzg_commitment initially appears like in Ghidra:
With just a little work, you’ll be able to rename variables and add feedback to make it simpler to learn. This is what it may appear like after a couple of minutes:
Static Evaluation
Clang comes built-in with the Clang Static Analyzer, which is a superb static evaluation instrument that may establish many issues that the compiler will miss. Because the identify “static” suggests, it examines code with out executing it. That is slower than the compiler, however loads sooner than “dynamic” evaluation instruments which execute code.
This is a easy instance which forgets to free arr (and has one other downside however we are going to speak extra about that later). The compiler is not going to establish this, even with all warnings enabled as a result of technically that is utterly legitimate code.
#embrace <stdlib.h> int essential(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
The unix.Malloc checker will establish that arr wasn’t freed. The road within the warning message is a bit deceptive, but it surely is sensible if you concentrate on it; the analyzer reached the return assertion and seen that the reminiscence hadn’t been freed.
Not all the findings are that easy although. This is a discovering that Clang Static Analyzer present in c-kzg-4844 when initially launched to the venture:
Given an surprising enter, it was attainable to shift this worth by 32 bits which is undefined conduct. The answer was to limit the enter with CHECK(log2_pow2(n) != 0) in order that this was unattainable. Good job, Clang Static Analyzer!
Sanitize
Santizers are dynamic evaluation instruments which instrument (add directions) to applications which may level out points throughout execution. These are significantly helpful at discovering widespread errors related to reminiscence dealing with. Clang comes built-in with a number of sanitizers; listed below are the 4 we discover most helpful and simple to make use of.
Deal with
AddressSanitizer (ASan) is a quick reminiscence error detector which may establish out-of-bounds accesses, use-after-free, use-after-return, use-after-scope, double-free, and reminiscence leaks.
Right here is similar instance from earlier. It forgets to free arr and it’ll set the sixth component in a 5 component array. It is a easy instance of a heap-buffer-overflow:
#embrace <stdlib.h> int essential(void) { int* arr = malloc(5 * sizeof(int)); arr[5] = 42; return 0; }
When compiled with -fsanitize=deal with and executed, it is going to output the next error message. This factors you in route (a 4-byte write in essential). This binary may very well be seen in a disassembler to determine precisely which instruction (at essential+0x84) is inflicting the issue.
Equally, this is an instance the place it finds a heap-use-after-free:
#embrace <stdlib.h> int essential(void) { int *arr = malloc(5 * sizeof(int)); free(arr); return arr[2]; }
It tells you that there is a 4-byte learn of freed reminiscence at essential+0x8c.
Reminiscence
MemorySanitizer (MSan) is a detector of uninitialized reads. This is a easy instance which reads (and returns) an uninitialized worth:
int essential(void) { int information[2]; return information[0]; }
When compiled with -fsanitize=reminiscence and executed, it is going to output the next error message:
Undefined Habits
UndefinedBehaviorSanitizer (UBSan) detects undefined conduct, which refers back to the state of affairs the place a program’s conduct is unpredictable and never specified by the langauge customary. Some widespread examples of this are accessing out-of-bounds reminiscence, dereferencing an invalid pointer, studying uninitialized variables, and overflow of a signed integer. For instance, right here we increment INT_MAX which is undefined conduct.
#embrace <limits.h> int essential(void) { int a = INT_MAX; return a + 1; }
When compiled with -fsanitize=undefined and executed, it is going to output the next error message which tells us precisely the place the issue is and what the situations are:
Thread
ThreadSanitizer (TSan) detects information races, which may happen in multi-threaded applications when two or extra threads entry a shared reminiscence location on the similar time. This example introduces unpredictability and may result in undefined conduct. This is an instance by which two threads increment a worldwide counter variable. There are no locks or semaphores, so it is totally attainable that these two threads will increment the variable on the similar time.
#embrace <pthread.h> int counter = 0; void *increment(void *arg) { (void)arg; for (int i = 0; i < 1000000; i++) counter++; return NULL; } int essential(void) { pthread_t thread1, thread2; pthread_create(&thread1, NULL, increment, NULL); pthread_create(&thread2, NULL, increment, NULL); pthread_join(thread1, NULL); pthread_join(thread2, NULL); return 0; }
When compiled with -fsanitize=thread and executed, it is going to output the next error message:
This error message tells us that there is a information race. In two threads, the increment perform is writing to the identical 4 bytes on the similar time. It even tells us that the reminiscence is counter.
Valgrind
Valgrind is a strong instrumentation framework for constructing dynamic evaluation instruments, however its greatest identified for figuring out reminiscence errors and leaks with its built-in Memcheck instrument.
The next picture exhibits the output from operating c-kzg-4844’s exams with Valgrind. Within the purple field is a legitimate discovering for a “conditional leap or transfer [that] is determined by uninitialized worth(s).”
This identified an edge case in expand_root_of_unity. If the flawed root of unity or width have been offered, it was attainable that the loop will break earlier than out[width] was initialized. On this state of affairs, the ultimate test would rely upon an uninitialized worth.
static C_KZG_RET expand_root_of_unity( fr_t *out, const fr_t *root, uint64_t width ) { out[0] = FR_ONE; out[1] = *root; for (uint64_t i = 2; !fr_is_one(&out[i - 1]); i++) { CHECK(i <= width); blst_fr_mul(&out[i], &out[i - 1], root); } CHECK(fr_is_one(&out[width])); return C_KZG_OK; }
Safety Evaluation
After improvement stabilizes, it has been completely examined, and your crew has manually reviewed the codebase themselves a number of instances, it is time to get a safety evaluation by a good safety group. This would possibly not be a stamp of approval, but it surely exhibits that your venture is at the least considerably safe. Be mindful there is no such thing as a such factor as excellent safety. There’ll at all times be the danger of vulnerabilities.
For c-kzg-4844 and go-kzg-4844, the Ethereum Basis contracted Sigma Prime to conduct a safety evaluation. They produced this report with 8 findings. It incorporates one essential vulnerability in go-kzg-4844 that was a extremely good discover. The BLS12-381 library that go-kzg-4844 makes use of, gnark-crypto, had a bug which allowed invalid G1 and G2 factors to be sucessfully decoded. Had this not been mounted, this might have resulted in a consensus bug (a disagreement between implementations) in Ethereum.
Bug Bounty
If a vulnerability in your venture may very well be exploited for positive factors, like it’s for Ethereum, contemplate organising a bug bounty program. This enables safety researchers, or anybody actually, to submit vulnerability studies in alternate for cash. Typically, that is particularly for findings which may show that an exploit is feasible. If the bug bounty payouts are cheap, bug finders will notify you of the bug moderately than exploiting it or promoting it to a different get together. We advocate beginning your bug bounty program after the findings from the primary safety evaluation are resolved; ideally, the safety evaluation would price lower than the bug bounty payouts.
Conclusion
The event of sturdy C tasks, particularly within the essential area of blockchain and cryptocurrencies, requires a multi-faceted method. Given the inherent vulnerabilities related to the C language, a mixture of greatest practices and instruments is crucial for producing resilient software program. We hope our experiences and findings from our work with c-kzg-4844 present invaluable insights and greatest practices for others embarking on comparable tasks.
